Positive correlation between transcriptomic stemness and PI3K/AKT/mTOR signaling scores in breast cancer, and a counterintuitive relationship with PIK3CA genotype

A PI3Kα-selective inhibitor has recently been approved for use in breast tumors harboring mutations in PIK3CA, the gene encoding p110α. Preclinical studies have suggested that the PI3K/AKT/mTOR signaling pathway influences stemness, a dedifferentiation-related cellular phenotype associated with aggressive cancer. However, to date, no direct evidence for such a correlation has been demonstrated in human tumors. In two independent human breast cancer cohorts, encompassing nearly 3,000 tumor samples, transcriptional footprint-based analysis uncovered a positive linear association between transcriptionally-inferred PI3K/AKT/mTOR signaling scores and stemness scores. Unexpectedly, stratification of tumors according to PIK3CA genotype revealed a “biphasic” relationship of mutant PIK3CA allele dosage with these scores. Relative to tumor samples without PIK3CA mutations, the presence of a single copy of a hotspot PIK3CA variant was associated with lower PI3K/AKT/mTOR signaling and stemness scores, whereas the presence of multiple copies of PIK3CA hotspot mutations correlated with higher PI3K/AKT/mTOR signaling and stemness scores. This observation was recapitulated in a human cell model of heterozygous and homozygous PIK3CAH1047R expression. Collectively, our analysis (1) provides evidence for a signaling strength-dependent PI3K-stemness relationship in human breast cancer; (2) supports evaluation of the potential benefit of patient stratification based on a combination of conventional PI3K pathway genetic information with transcriptomic indices of PI3K signaling activation. Author summary Breast cancers often have increased activity of the so-called PI3Kα enzyme and the pathway it activates, usually attributed to genetic alterations in the PIK3CA gene, encoding a critical PI3Kα component. Recent cell studies have shown that effects of a PIK3CA mutation depend on how many copies are present. For example, two copies of a strong mutation, but not one, fix cells in a state of “stemness”, a property associated with tumor aggressiveness and therapy failure. To determine relationships among PI3K genetic variation, PI3K activity and stemness in breast cancers we used data from independent patient cohorts encompassing nearly 3,000 tumors. Using PI3K signaling or stemness scores derived from gene expression data, we found a strong, positive association between the scores: aggressive tumors show the highest scores. In contrast, the relationship of these scores with PIK3CA mutation status was unexpected–cancers with one PIK3CA mutant copy showed a decrease in both scores, while they increased in cancers with additional copies. This was confirmed in cellular models. This suggests that using binary information about a PIK3CA mutation to define patient groups for trials may miss important effects of allele dosage. We suggest that grouping may be improved by combining PIK3CA mutational information with functional indices of PI3K pathway activation.